What Is Self-Querying Retrieval?
Self-querying retrieval (SQR) is a method ensuring that LLMs are at the core of understanding the user’s intent against a document collection. Key ideas include:
- Document representation: Word embedding provides a numerical vector for every document. This helps in fast comparison between the documents.
- User query: The user submits a natural language query expressing their need for information.
- LLM-driven retrieval: The query and the document representations are fed into the LLM, which then retrieves documents that maximize the user’s intent.
- Refine and repeat: The user is now able to refine his query or ask follow-up questions to narrow the search based on the retrieved documents.
Why Self-Querying Retrieval?
Traditional retrieval systems usually require complex query languages or predefined search facets. However, self-querying retrieval would provide a much more natural and user-friendly approach. Here is why:
https://dzone.com/articles/optimizing-search-precision-with-sqr-and-langchain
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